Method for improving a process for a patterning process

ABSTRACT

A method for improving a process model for a patterning process, the method including obtaining a) a measured contour from an image capture device, and b) a simulated contour generated from a simulation of the process model. The method also includes aligning the measured contour with the simulated contour by determining an offset between the measured contour and the simulated contour. The process model is calibrated to reduce a difference, computed based on the determined offset, between the simulated contour and the measured contour.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority of U.S. application 62/680,284 whichwas filed on Jun. 4, 2018, and which is incorporated herein in itsentirety by reference.

TECHNICAL FIELD

The description herein relates generally to metrology as used withprocess models for lithographic processes, and more particularly,apparatuses, methods, and computer program products for improvingprocess models through image alignment methods.

BACKGROUND

A lithographic projection apparatus can be used, for example, in themanufacture of integrated circuits (ICs). In such a case, a patterningdevice (e.g., a mask) may contain or provide a pattern corresponding toan individual layer of the IC (“design layout”), and this pattern can betransferred onto a target portion (e.g. comprising one or more dies) ona substrate (e.g., silicon wafer) that has been coated with a layer ofradiation-sensitive material (“resist”), by methods such as irradiatingthe target portion through the pattern on the patterning device. Ingeneral, a single substrate contains a plurality of adjacent targetportions to which the pattern is transferred successively by thelithographic projection apparatus, one target portion at a time. In onetype of lithographic projection apparatuses, the pattern on the entirepatterning device is transferred onto one target portion in one go; suchan apparatus is commonly referred to as a stepper. In an alternativeapparatus, commonly referred to as a step-and-scan apparatus, aprojection beam scans over the patterning device in a given referencedirection (the “scanning” direction) while synchronously moving thesubstrate parallel or anti-parallel to this reference direction.Different portions of the pattern on the patterning device aretransferred to one target portion progressively. Since, in general, thelithographic projection apparatus will have a reduction ratio M (e.g.,4), the speed F at which the substrate is moved will be 1/M times thatat which the projection beam scans the patterning device. Moreinformation with regard to lithographic devices can be found in, forexample, U.S. Pat. No. 6,046,792, incorporated herein by reference.

Prior to transferring the pattern from the patterning device to thesubstrate, the substrate may undergo various procedures, such aspriming, resist coating and a soft bake. After exposure, the substratemay be subjected to other procedures (“post-exposure procedures”), suchas a post-exposure bake (PEB), development, a hard bake andmeasurement/inspection of the transferred pattern. This array ofprocedures is used as a basis to make an individual layer of a device,e.g., an IC. The substrate may then undergo various processes such asetching, ion-implantation (doping), metallization, oxidation,chemo-mechanical polishing, etc., all intended to finish off theindividual layer of the device. If several layers are required in thedevice, then the whole procedure, or a variant thereof, is repeated foreach layer. Eventually, a device will be present in each target portionon the substrate. These devices are then separated from one another by atechnique such as dicing or sawing, whence the individual devices can bemounted on a carrier, connected to pins, etc.

Thus, manufacturing devices, such as semiconductor devices, typicallyinvolve processing a substrate (e.g., a semiconductor wafer) using anumber of fabrication processes to form various features and multiplelayers of the devices. Such layers and features are typicallymanufactured and processed using, e.g., deposition, lithography, etch,chemical-mechanical polishing, and ion implantation. Multiple devicesmay be fabricated on a plurality of dies on a substrate and thenseparated into individual devices. This device manufacturing process maybe considered a patterning process. A patterning process involves apatterning step, such as optical and/or nanoimprint lithography using apatterning device in a lithographic apparatus, to transfer a pattern onthe patterning device to a substrate and typically, but optionally,involves one or more related pattern processing steps, such as resistdevelopment by a development apparatus, baking of the substrate using abake tool, etching using the pattern using an etch apparatus, etc.

As noted, lithography is a central step in the manufacturing of devicesuch as ICs, where patterns formed on substrates define functionalelements of the devices, such as microprocessors, memory chips, etc.Similar lithographic techniques are also used in the formation of flatpanel displays, micro-electro mechanical systems (MEMS) and otherdevices.

As semiconductor manufacturing processes continue to advance, thedimensions of functional elements have continually been reduced whilethe amount of functional elements, such as transistors, per device hasbeen steadily increasing over decades, following a trend commonlyreferred to as “Moore's law.” At the current state of technology, layersof devices are manufactured using lithographic projection apparatusesthat project a design layout onto a substrate using illumination from adeep-ultraviolet illumination source, creating individual functionalelements having dimensions well below 100 nm, i.e. less than half thewavelength of the radiation from the illumination source (e.g., a 193 nmillumination source).

This process in which features with dimensions smaller than theclassical resolution limit of a lithographic projection apparatus areprinted, is commonly known as low-k1 lithography, according to theresolution formula CD=k1×λ/NA, where λ is the wavelength of radiationemployed (currently in most cases 248 nm or 193 nm), NA is the numericalaperture of projection optics in the lithographic projection apparatus,CD is the “critical dimension”—generally the smallest feature sizeprinted—and k1 is an empirical resolution factor. In general, thesmaller k1 the more difficult it becomes to reproduce a pattern on thesubstrate that resembles the shape and dimensions planned by a designerin order to achieve particular electrical functionality and performance.To overcome these difficulties, sophisticated fine-tuning steps areapplied to the lithographic projection apparatus, the design layout, orthe patterning device. These include, for example, but not limited to,optimization of NA and optical coherence settings, customizedillumination schemes, use of phase shifting patterning devices, opticalproximity correction (OPC, sometimes also referred to as “optical andprocess correction”) in the design layout, or other methods generallydefined as “resolution enhancement techniques” (RET).

The term “projection optics,” as used herein, should be broadlyinterpreted as encompassing various types of optical systems, includingrefractive optics, reflective optics, apertures and catadioptric optics,for example. The term “projection optics” may also include componentsoperating according to any of these design types for directing, shapingor controlling the projection beam of radiation, collectively orsingularly. The term “projection optics” may include any opticalcomponent in the lithographic projection apparatus, no matter where theoptical component is located on an optical path of the lithographicprojection apparatus. Projection optics may include optical componentsfor shaping, adjusting and/or projecting radiation from the sourcebefore the radiation passes the patterning device, and/or opticalcomponents for shaping, adjusting and/or projecting the radiation afterthe radiation passes the patterning device. The projection opticsgenerally exclude the source and the patterning device.

SUMMARY

A method for improving a process model for a patterning process includesobtaining a) a measured contour from an image capture device, and b) asimulated contour generated from a simulation of the process model. Themethod also includes aligning the measured contour with the simulatedcontour by determining an offset between the measured contour and thesimulated contour. The process model is calibrated to reduce adifference, computed based on the determined offset, between thesimulated contour and the measured contour.

In some variations, the offset can be further determined based onmeasurement coordinates substantially defining a portion of the measuredcontour. Also, the offset can be further determined based on distancesbetween the measurement coordinates and the simulated contour, thedistances being in directions perpendicular to the measured contour atthe measurement coordinates. The aligning can further include reducing acost function calculated based on the distances.

In other variations, an edge placement (EP) coordinate can be generatedon the measured contour, where the offset can be further determinedbased on the EP coordinate. The EP coordinate can be generated byinterpolating between two or more measurement coordinates. The EPcoordinate can be generated by extrapolating from two or moremeasurement coordinates. Accordingly, the calibrating can furtherinclude modifying a feature of the process model to reduce thedifference, the modifying causing a change to a shape of the simulatedcontour.

In some variations, the measured contour can be identified based on achange in intensity of pixels in the measured image. The identifying canbe based on the change exceeding a greyscale threshold.

In yet other variations, the model can include obtaining the simulatedcontour from Graphic Database Systems (GDS) polygons and also convertingedge placement coordinates or measurement coordinates comprising themeasured contour into GDS coordinates. The GDS polygons can be in one ormore formats selected from GDS stream format (GDSII) and Open ArtworkSystem Interchange Standard (OASIS).

In an interrelated aspect, a method for improving an optical proximitycorrection (OPC) model for a patterning process includes obtaining a) ameasured contour from an image capture device, and b) a simulatedcontour generated from a simulation of the OPC model. The method alsoincludes aligning the measured contour with the simulated contour bydetermining an offset between the measured contour and the simulatedcontour. Additionally, the method also includes modifying features ofthe OPC model to reduce a difference, computed based on the determinedoffset, between the simulated contour and the measured contour.

In some variations, the features include one or more of a diffusionrate, a diffusion range, a deprotection ratio, and an acid/baseconcentration. The method can also include obtaining the simulatedcontour based on the simulation of the OPC model, wherein the OPC modelis a preliminary model that includes an optical model and does notinclude a resist model.

In other variations, the method can include obtaining an initialsimulated contour with a preliminary model that includes an opticalmodel and a resist model and modifying features of the resist model toreduce the difference between the initial simulated contour and themeasured contour.

In an interrelated aspect, a method for improving a process model for apatterning process includes obtaining a) a measured images from an imagecapture device, and b) a simulated contour generated from a simulationof the process model. The method also includes, aligning the measuredimages, generating a combined measured image from the aligned pluralityof measured images, extracting a measured contour from the combinedmeasured image by an image analysis method, aligning the measuredcontour with the simulated contour by determining an offset between themeasured contour and the simulated contour, and calibrating the processmodel to reduce a difference, computed based on the determined offset,between the simulated contour and the measured contour.

In some variations, the combined image can be generated by averaging thealigned measured images. The measured images can be obtained fromprinted patterns from at least two different dies manufactured from atarget pattern. Each of the measured images generating the combinedimage can be acquired by scanning a different die.

In other variations, the image capture device can be a scanning electronmicroscope. Obtaining the measured images can be performed by scanningan electron beam over a printed pattern at a number of angles, includingapproximately +45 degrees and −45 degrees. Also, half of the measuredimages can be scanned at approximately +45 degrees and another half ofthe measured images can be scanned at approximately −45 degrees.

In other variations, the obtaining can be performed with the scanningelectron microscope operating at a dosage below that required to obtaina scan sufficient to resolve a critical dimension. The image capturedevice can be an electron beam inspection system. The electron beaminspection system can have a large field of view and the measured imagescan be obtained at least partially from within the large field of view.The large field of view can be approximately 1-50 microns on a side orapproximately 6-12 microns on a side. The electron beam inspectionsystem can detect hotspots or weak-points in a printed pattern.

In yet other variations, the method can further include determining acommon area in the plurality of measured images captured from the imagecapture device and generating the combined measured image based on thecommon area.

According to an embodiment, there is provided a computer program productcomprising a non-transitory computer readable medium having instructionsrecorded thereon. The instructions, when executed by a computer,implement the methods listed in the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, show certain aspects of the subject matterdisclosed herein and, together with the description, help explain someof the principles associated with the disclosed embodiments. In thedrawings,

FIG. 1 illustrates a block diagram of various subsystems of alithographic projection apparatus, according to an embodiment.

FIG. 2 illustrates an exemplary flow chart for simulating lithography ina lithographic projection apparatus, according to an embodiment.

FIG. 3 illustrates an exemplary measured contour obtained from an imageof a printed pattern, according to an embodiment.

FIG. 4 illustrates an exemplary method of generating a measured contourby averaging multiple images, according to an embodiment.

FIG. 5 illustrates an exemplary method of aligning a measured contourwith a simulated contour, according to an embodiment.

FIG. 6 illustrates an exemplary method of determining an offset betweena measured contour and a simulated contour, according to an embodiment.

FIG. 7 illustrates an exemplary improvement of matching a simulatedcontour to a measured contour, according to an embodiment.

FIG. 8 illustrates an exemplary improvement in alignment based onimproving a preliminary model, according to an embodiment.

FIG. 9 illustrates an exemplary method of calibrating a process model,according to an embodiment.

FIG. 10 illustrates an exemplary method of calibrating an OPC model,according to an embodiment.

FIG. 11 illustrates an exemplary method of acquiring multiple images ofa target and calibrating a process model, according to an embodiment.

FIG. 12 is a block diagram of an example computer system, according toan embodiment.

FIG. 13 is a block diagram of an example metrology system, according toan embodiment.

FIG. 14 is a process flow diagram of an example implementation of animproved metrology process, according to an embodiment.

FIG. 15 is a schematic diagram of a lithographic projection apparatus,according to an embodiment.

FIG. 16 is a schematic diagram of another lithographic projectionapparatus, according to an embodiment.

FIG. 17 is a detailed view of the lithographic projection apparatus,according to an embodiment.

FIG. 18 is a detailed view of the source collector module of thelithographic projection apparatus, according to an embodiment.

FIG. 19 schematically depicts an embodiment of an electron beaminspection apparatus, according to an embodiment.

FIG. 20 schematically illustrates a further embodiment of an inspectionapparatus, according to an embodiment.

DETAILED DESCRIPTION

Although specific reference may be made in this text to the manufactureof ICs, it should be explicitly understood that the description hereinhas many other possible applications. For example, it may be employed inthe manufacture of integrated optical systems, guidance and detectionpatterns for magnetic domain memories, liquid-crystal display panels,thin-film magnetic heads, etc. The skilled artisan will appreciate that,in the context of such alternative applications, any use of the terms“reticle”, “wafer” or “die” in this text should be considered asinterchangeable with the more general terms “mask”, “substrate” and“target portion”, respectively.

In the present document, the terms “radiation” and “beam” are used toencompass all types of electromagnetic radiation, including ultravioletradiation (e.g. with a wavelength of 365, 248, 193, 157 or 126 nm) andEUV (extreme ultra-violet radiation, e.g. having a wavelength in therange of about 5-100 nm).

The patterning device can comprise, or can form, one or more designlayouts. The design layout can be generated utilizing CAD(computer-aided design) programs, this process often being referred toas EDA (electronic design automation). Most CAD programs follow a set ofpredetermined design rules in order to create functional designlayouts/patterning devices. These rules are set by processing and designlimitations. For example, design rules define the space tolerancebetween devices (such as gates, capacitors, etc.) or interconnect lines,so as to ensure that the devices or lines do not interact with oneanother in an undesirable way. One or more of the design rulelimitations may be referred to as “critical dimension” (CD). A criticaldimension of a device can be defined as the smallest width of a line orhole or the smallest space between two lines or two holes. Thus, the CDdetermines the overall size and density of the designed device. Ofcourse, one of the goals in device fabrication is to faithfullyreproduce the original design intent on the substrate (via thepatterning device).

The term “mask” or “patterning device” as employed in this text may bebroadly interpreted as referring to a generic patterning device that canbe used to endow an incoming radiation beam with a patternedcross-section, corresponding to a pattern that is to be created in atarget portion of the substrate; the term “light valve” can also be usedin this context. Besides the classic mask (transmissive or reflective;binary, phase-shifting, hybrid, etc.), examples of other such patterningdevices include a programmable mirror array and a programmable LCDarray.

An example of a programmable mirror array can be a matrix-addressablesurface having a viscoelastic control layer and a reflective surface.The basic principle behind such an apparatus is that (for example)addressed areas of the reflective surface reflect incident radiation asdiffracted radiation, whereas unaddressed areas reflect incidentradiation as undiffracted radiation. Using an appropriate filter, thesaid undiffracted radiation can be filtered out of the reflected beam,leaving only the diffracted radiation behind; in this manner, the beambecomes patterned according to the addressing pattern of thematrix-addressable surface. The required matrix addressing can beperformed using suitable electronic means.

An example of a programmable LCD array is given in U.S. Pat. No.5,229,872, which is incorporated herein by reference.

FIG. 1 illustrates a block diagram of various subsystems of alithographic projection apparatus 10A, according to an embodiment. Majorcomponents are a radiation source 12A, which may be a deep-ultravioletexcimer laser source or other type of source including an extreme ultraviolet (EUV) source (as discussed above, the lithographic projectionapparatus itself need not have the radiation source), illuminationoptics which, e.g., define the partial coherence (denoted as sigma) andwhich may include optics 14A, 16Aa and 16Ab that shape radiation fromthe source 12A; a patterning device 18A; and transmission optics 16Acthat project an image of the patterning device pattern onto a substrateplane 22A. An adjustable filter or aperture 20A at the pupil plane ofthe projection optics may restrict the range of beam angles that impingeon the substrate plane 22A, where the largest possible angle defines thenumerical aperture of the projection optics NA=n sin(Θ_(max)), wherein nis the refractive index of the media between the substrate and the lastelement of the projection optics, and Θ_(max) is the largest angle ofthe beam exiting from the projection optics that can still impinge onthe substrate plane 22A.

In a lithographic projection apparatus, a source provides illumination(i.e. radiation) to a patterning device and projection optics direct andshape the illumination, via the patterning device, onto a substrate. Theprojection optics may include at least some of the components 14A, 16Aa,16Ab and 16Ac. An aerial image (AI) is the radiation intensitydistribution at substrate level. A resist model can be used to calculatethe resist image from the aerial image, an example of which can be foundin U.S. Patent Application Publication No. US 2009-0157630, thedisclosure of which is hereby incorporated by reference in its entirety.The resist model is related only to properties of the resist layer(e.g., effects of chemical processes which occur during exposure,post-exposure bake (PEB) and development). Optical properties of thelithographic projection apparatus (e.g., properties of the illumination,the patterning device and the projection optics) dictate the aerialimage and can be defined in an optical model. Since the patterningdevice used in the lithographic projection apparatus can be changed, itis desirable to separate the optical properties of the patterning devicefrom the optical properties of the rest of the lithographic projectionapparatus including at least the source and the projection optics.Details of techniques and models used to transform a design layout intovarious lithographic images (e.g., an aerial image, a resist image,etc.), apply OPC using those techniques and models and evaluateperformance (e.g., in terms of process window) are described in U.S.Patent Application Publication Nos. US 2008-0301620, 2007-0050749,2007-0031745, 2008-0309897, 2010-0162197, and 2010-0180251, thedisclosure of each which is hereby incorporated by reference in itsentirety.

One aspect of understanding a lithographic process is understanding theinteraction of the radiation and the patterning device. Theelectromagnetic field of the radiation after the radiation passes thepatterning device may be determined from the electromagnetic field ofthe radiation before the radiation reaches the patterning device and afunction that characterizes the interaction. This function may bereferred to as the mask transmission function (which can be used todescribe the interaction by a transmissive patterning device and/or areflective patterning device).

The mask transmission function may have a variety of different forms.One form is binary. A binary mask transmission function has either oftwo values (e.g., zero and a positive constant) at any given location onthe patterning device. A mask transmission function in the binary formmay be referred to as a binary mask. Another form is continuous. Namely,the modulus of the transmittance (or reflectance) of the patterningdevice is a continuous function of the location on the patterningdevice. The phase of the transmittance (or reflectance) may also be acontinuous function of the location on the patterning device. A masktransmission function in the continuous form may be referred to as acontinuous tone mask or a continuous transmission mask (CTM). Forexample, the CTM may be represented as a pixelated image, where eachpixel may be assigned a value between 0 and 1 (e.g., 0.1, 0.2, 0.3,etc.) instead of binary value of either 0 or 1. In an embodiment, CTMmay be a pixelated gray scale image, where each pixel having values(e.g., within a range [−255, 255], normalized values within a range [0,1] or [−1, 1] or other appropriate ranges).

The thin-mask approximation, also called the Kirchhoff boundarycondition, is widely used to simplify the determination of theinteraction of the radiation and the patterning device. The thin-maskapproximation assumes that the thickness of the structures on thepatterning device is very small compared with the wavelength and thatthe widths of the structures on the mask are very large compared withthe wavelength. Therefore, the thin-mask approximation assumes theelectromagnetic field after the patterning device is the multiplicationof the incident electromagnetic field with the mask transmissionfunction. However, as lithographic processes use radiation of shorterand shorter wavelengths, and the structures on the patterning devicebecome smaller and smaller, the assumption of the thin-maskapproximation can break down. For example, interaction of the radiationwith the structures (e.g., edges between the top surface and a sidewall)because of their finite thicknesses (“mask 3D effect” or “M3D”) maybecome significant. Encompassing this scattering in the masktransmission function may enable the mask transmission function tobetter capture the interaction of the radiation with the patterningdevice. A mask transmission function under the thin-mask approximationmay be referred to as a thin-mask transmission function. A masktransmission function encompassing M3D may be referred to as a M3D masktransmission function.

According to an embodiment of the present disclosure, one or more imagesmay be generated. The images includes various types of signal that maybe characterized by pixel values or intensity values of each pixel.Depending on the relative values of the pixel within the image, thesignal may be referred as, for example, a weak signal or a strongsignal, as may be understood by a person of ordinary skill in the art.The term “strong” and “weak” are relative terms based on intensityvalues of pixels within an image and specific values of intensity maynot limit scope of the present disclosure. In an embodiment, the strongand weak signal may be identified based on a selected threshold value.In an embodiment, the threshold value may be fixed (e.g., a midpoint ofa highest intensity and a lowest intensity of pixel within the image. Inan embodiment, a strong signal may refer to a signal with values greaterthan or equal to an average signal value across the image and a weaksignal may refer to signal with values less than the average signalvalue. In an embodiment, the relative intensity value may be based onpercentage. For example, the weak signal may be signal having intensityless than 50% of the highest intensity of the pixel (e.g., pixelscorresponding to target pattern may be considered pixels with highestintensity) within the image. Furthermore, each pixel within an image mayconsidered as a variable. According to the present embodiment,derivatives or partial derivative may be determined with respect to eachpixel within the image and the values of each pixel may be determined ormodified according to a cost function based evaluation and/or gradientbased computation of the cost function. For example, a CTM image mayinclude pixels, where each pixel is a variable that can take any realvalue.

FIG. 2 illustrates an exemplary flow chart for simulating lithography ina lithographic projection apparatus, according to an embodiment. Sourcemodel 31 represents optical characteristics (including radiationintensity distribution and/or phase distribution) of the source.Projection optics model 32 represents optical characteristics (includingchanges to the radiation intensity distribution and/or the phasedistribution caused by the projection optics) of the projection optics.Design layout model 35 represents optical characteristics of a designlayout (including changes to the radiation intensity distribution and/orthe phase distribution caused by design layout 33), which is therepresentation of an arrangement of features on or formed by apatterning device. Aerial image 36 can be simulated from design layoutmodel 35, projection optics model 32, and design layout model 35. Resistimage 38 can be simulated from aerial image 36 using resist model 37.Simulation of lithography can, for example, predict contours and CDs inthe resist image.

More specifically, it is noted that source model 31 can represent theoptical characteristics of the source that include, but not limited to,numerical aperture settings, illumination sigma (c) settings as well asany particular illumination shape (e.g. off-axis radiation sources suchas annular, quadrupole, dipole, etc.). Projection optics model 32 canrepresent the optical characteristics of the projection optics,including aberration, distortion, one or more refractive indexes, one ormore physical sizes, one or more physical dimensions, etc. Design layoutmodel 35 can represent one or more physical properties of a physicalpatterning device, as described, for example, in U.S. Pat. No.7,587,704, which is incorporated by reference in its entirety. Theobjective of the simulation is to accurately predict, for example, edgeplacement, aerial image intensity slope and/or CD, which can then becompared against an intended design. The intended design is generallydefined as a pre-OPC design layout which can be provided in astandardized digital file format such as GDSII or OASIS or other fileformat.

From this design layout, one or more portions may be identified, whichare referred to as “clips”. In an embodiment, a set of clips isextracted, which represents the complicated patterns in the designlayout (typically about 50 to 1000 clips, although any number of clipsmay be used). These patterns or clips represent small portions (i.e.circuits, cells or patterns) of the design and more specifically, theclips typically represent small portions for which particular attentionand/or verification is needed. In other words, clips may be the portionsof the design layout, or may be similar or have a similar behavior ofportions of the design layout, where one or more critical features areidentified either by experience (including clips provided by acustomer), by trial and error, or by running a full-chip simulation.Clips may contain one or more test patterns or gauge patterns.

An initial larger set of clips may be provided a priori by a customerbased on one or more known critical feature areas in a design layoutwhich require particular image optimization. Alternatively, in anotherembodiment, an initial larger set of clips may be extracted from theentire design layout by using some kind of automated (such as machinevision) or manual algorithm that identifies the one or more criticalfeature areas.

In a lithographic projection apparatus, as an example, a cost functionmay be expressed as

CF(z ₁ ,z ₂ , . . . ,z _(N))=Σ_(p=1) ^(P) w _(p) f _(p) ²(z ₁ ,z ₂ , . .. ,z _(N))  (Eq. 1)

where (z₁, z₂, . . . , z_(N)) are N design variables or values thereof.f_(p)(z₁, z₂, . . . , z_(N)) can be a function of the design variables(z₁, z₂, . . . , z_(N)) such as a difference between an actual value andan intended value of a characteristic for a set of values of the designvariables of (z₁, z₂, . . . , z_(N)). w_(p) is a weight constantassociated with f_(p)(z₁, z₂, . . . , z_(N)). For example, thecharacteristic may be a position of an edge of a pattern, measured at agiven point on the edge. Different f_(p)(z₁, z₂, . . . , z_(N)) may havedifferent weight w_(p). For example, if a particular edge has a narrowrange of permitted positions, the weight w_(p) for the f_(p)(z₁, z₂, . .. , z_(N)) representing the difference between the actual position andthe intended position of the edge may be given a higher value. f_(p)(z₁,z₂, . . . , z_(N)) can also be a function of an interlayercharacteristic, which is in turn a function of the design variables (z₁,z₂, . . . , z_(N)). Of course, CF(z₁, z₂, . . . , z_(N)) is not limitedto the form in Eq. 1. CF(z₁, z₂, . . . , z_(N)) can be in any othersuitable form.

The cost function may represent any one or more suitable characteristicsof the lithographic projection apparatus, lithographic process or thesubstrate, for instance, focus, CD, image shift, image distortion, imagerotation, stochastic variation, throughput, local CD variation, processwindow, an interlayer characteristic, or a combination thereof. In oneembodiment, the design variables (z₁, z₂, . . . , z_(N)) comprise one ormore selected from dose, global bias of the patterning device, and/orshape of illumination. Since it is the resist image that often dictatesthe pattern on a substrate, the cost function may include a functionthat represents one or more characteristics of the resist image. Forexample, f_(p)(z₁, z₂, . . . , z_(N)) can be simply a distance between apoint in the resist image to an intended position of that point (i.e.,edge placement error EPE_(p)(z₁, z₂, . . . , z_(N)). The designvariables can include any adjustable parameter such as an adjustableparameter of the source, the patterning device, the projection optics,dose, focus, etc.

The lithographic apparatus may include components collectively called a“wavefront manipulator” that can be used to adjust the shape of awavefront and intensity distribution and/or phase shift of a radiationbeam. In an embodiment, the lithographic apparatus can adjust awavefront and intensity distribution at any location along an opticalpath of the lithographic projection apparatus, such as before thepatterning device, near a pupil plane, near an image plane, and/or neara focal plane. The wavefront manipulator can be used to correct orcompensate for certain distortions of the wavefront and intensitydistribution and/or phase shift caused by, for example, the source, thepatterning device, temperature variation in the lithographic projectionapparatus, thermal expansion of components of the lithographicprojection apparatus, etc. Adjusting the wavefront and intensitydistribution and/or phase shift can change values of the characteristicsrepresented by the cost function. Such changes can be simulated from amodel or actually measured. The design variables can include parametersof the wavefront manipulator.

The design variables may have constraints, which can be expressed as(z₁, z₂, . . . , z_(N))∈Z, where Z is a set of possible values of thedesign variables. One possible constraint on the design variables may beimposed by a desired throughput of the lithographic projectionapparatus. Without such a constraint imposed by the desired throughput,the optimization may yield a set of values of the design variables thatare unrealistic. For example, if the dose is a design variable, withoutsuch a constraint, the optimization may yield a dose value that makesthe throughput economically impossible. However, the usefulness ofconstraints should not be interpreted as a necessity. For example, thethroughput may be affected by the pupil fill ratio. For someillumination designs, a low pupil fill ratio may discard radiation,leading to lower throughput. Throughput may also be affected by theresist chemistry. Slower resist (e.g., a resist that requires higheramount of radiation to be properly exposed) leads to lower throughput.

As used herein, the term “patterning process” generally means a processthat creates an etched substrate by the application of specifiedpatterns of light as part of a lithography process. However, “patterningprocess” can also include plasma etching, as many of the featuresdescribed herein can provide benefits to forming printed patterns usingplasma processing.

As used herein, the term “target pattern” means an idealized patternthat is to be etched on a substrate.

As used herein, the term “printed pattern” means the physical pattern ona substrate that was etched based on a target pattern. The printedpattern can include, for example, troughs, channels, depressions, edges,or other two and three dimensional features resulting from a lithographyprocess.

As used herein, the term “process model” means a model that includes oneor more models that simulate a patterning process. For example, aprocess model can include an optical model (e.g., that models a lenssystem/projection system used to deliver light in a lithography processand may include modelling the final optical image of light that goesonto a photoresist), a resist model (e.g., that models physical effectsof the resist, such as chemical effects due to the light), and an OPCmodel (e.g., that can be used to make target patterns and may includesub-resolution resist features (SRAFs), etc.).

As used herein, the term “calibrating” means to modify (e.g., improve ortune) and/or validate something, such as the process model.

The present disclosure describes, among other things, methods forimproving a process model for a patterning process. Improving metrologyduring process model calibration can include obtaining accurate imagesof a printed pattern (e.g., a printed wafer or portion thereof) that isbased on a target pattern. From the images, contours can be extractedthat correspond to features on the printed pattern. The contours (alsoreferred to as measured contours) can then be aligned to simulatedcontours, generated by the process model, to allow for calibration ofthe process model. The process model can be improved by adjustingparameters in the process model such that the simulated contours moreaccurately match the measured contours.

FIG. 3 illustrates an exemplary measured contour 330 obtained from animage of a printed pattern, according to an embodiment.

Lithographic processes can create of printed patterns (e.g., circuitpatterns for integrated circuits or computer chips) based on, forexample, target pattern 310 (shown in the top panel of FIG. 3). Due tolimitations in the patterning process, a printed pattern will generallyonly be an approximation of the target pattern 310.

A printed pattern can be imaged by an image capture device to generatemeasured image 320 (shown in the middle panel of FIG. 3), which containscontours that correspond to the idealized shapes in target pattern 310.In one embodiment, a method can include obtaining measured contour 330from an image capture device, for example, a scanning electronmicroscope (also referred to as an electron beam inspection system).Exemplary embodiments of an electron beam inspection system aredescribed in further detail with reference to FIGS. 19 and 20. Theelectron beam inspection system can be similar to scanning electronmicroscope but have a large field of view (LFOV) and high throughput forobtaining measured image 320. One non-limiting example of an electronbeam inspection system can be an HMI eP5, specifically configured tohave a LFOV. In some embodiments, a LFOV can measure, on a side, forexample, approximately 1-1000 microns, 100-500 microns, 1-50 microns,6-12 microns, etc. The image capture device can be configured to detecthotspots and/or weak-points in the printed pattern as well as gates andactive areas of a memory array, such as a static random access memory(SRAM). As illustrated in FIG. 3, measured image 320 resembles theprinted pattern, but the rectangular features in measured image 320 showrounding and slightly distorted lines. In other embodiments, the

Some embodiments can include identifying measured contour 330 (shown inthe bottom panel of FIG. 3) based on a change in intensity of pixels inmeasured image 320. Image analysis techniques can be used to identifymeasured contour 330 in measured image 320. Changes in intensity,gradient, and the like, can identify a change in height (or depth) offeatures in printed pattern, for example as used with edgedetermination. For example, when the measured image is expressed as agreyscale image, when the change exceeds a greyscale threshold (i.e., anintensity above or below a defined value), this can identify an edge(i.e. measured contour 330).

FIG. 4 illustrates an exemplary method of generating measured contour330 by averaging multiple images, according to an embodiment.

As described above, measured contour 330 can be extracted from a singlemeasured image 320. However, in other embodiments, multiple images of aprinted pattern can be combined into a combined image 420. Combiningimages reduce the effects of noise or other forms of error that can bepresent in any single image. In one embodiment, combined image 420 canbe generated by averaging multiple measured images 410. In otherembodiments, multiple measured images 410 can be aligned beforecombining or averaging. Image alignment can be based on, for example,image registration (such as using registration marks) of multiplemeasured images 410, an image analysis program determining a best matchbetween multiple measured images 410, calculating a correlationcoefficient based on multiple measured images 410, etc.

Once multiple measured images 410 captured from the image capture deviceare aligned, a common area can be determined. As used herein, the term“common area” means a collection of pixels in the multiple measuredimages 410 that refer to the same physical area of the printed pattern.Subsequently, combined measured image 320 can be generated based on thecommon area. This can cause some images, which may have a larger orsmaller field of view, to have edge pixels removed such that theaveraging procedure is uniform (i.e. the same number of pixels areaveraged at each pixel).

Resist shrinkage from repeated electron beam exposure can occur whenacquiring multiple images. Resist shrinkage can be reduced, for example,by embodiments where multiple measured images 410 are obtained fromprinted patterns from at least two different dies manufactured from atarget pattern. As used herein, the term “die” or “dies” means a blockof semiconducting material on which a given functional circuit is, orwill be, fabricated. In such embodiments, the dies have a similarprinted pattern, and thus can be used to generate substantiallyequivalent images while reducing physical exposure of the printedpattern to the electron beam. In other embodiments, each of the multiplemeasured images 410 generating combined image 420 can be acquired byscanning a different die. In this way, each image used in generating thecombined image 420 is based on a single printed pattern. In this way, insome embodiments, resist shrinkage can be reduced by obtaining measuredimage 320 with the scanning electron microscope operating at a dosagebelow that required to obtain a scan sufficient to resolve a criticaldimension.

In some embodiments, obtaining measured images 320 can be performed byscanning an electron beam over a printed pattern at several angles. Theangles can include approximately +45 degrees and −45 degrees. As usedherein, the term “approximately” (for example with reference to scanningangles) means the exact angle or an angle very close to the exact angle(e.g., within a few degrees or tenths of degrees). In anotherembodiment, half of the measured images 320 can be scanned atapproximately +45 degrees and another half of the measured images 320can be scanned at approximately −45 degrees.

FIG. 5 illustrates an exemplary method of aligning measured contour 330with simulated contour 510, according to an embodiment.

Process models that simulate a printed pattern can include anycombination of resist models, optical models, optical proximitycorrection models, etc. Accordingly, simulated contour 510 can begenerated from a simulation of the process model. As used herein,“simulated contour 510” means a contour that is generated by one or morecomputational models and represents a predicted outcome (whether a finalstage or an intermediate stage) of a lithography process.

To calibrate a process model, measured contours 330 can be compared withsimulated contours 510. As part of the calibration process, measuredcontour 330 can be aligned with simulated contour 510. In the example ofFIG. 5, measured contour 330 (as represented in this specificillustration by a graphical representation of measured image 320) can becompared with simulated contour 510. In the upper diagram of FIG. 5,measured contour 330 is not aligned properly with simulated contour 510.Measured contour 330 can be translated and/or rotated over simulatedcontour 510 until measured contour 330 is in approximately the correctposition, as shown in the lower diagram of FIG. 5. This can provide acoarse alignment which can be further improved upon as described below.

FIG. 6 illustrates an exemplary method of determining offset 610 betweenmeasured contour 330 and simulated contour 510, according to anembodiment.

Other alignment methods can be implemented, for example, after thecoarse alignment described above with reference to FIG. 5. Suchimplementations can include aligning measured contour 330 with simulatedcontour 510 by determining offset 610 between measured contour 330 andsimulated contour 510. As used herein, “offset 610” means a distancebetween a point on measured contour 330, and another point on simulatedcontour 510. The present disclosure provides various methods fordetermining offset 610. For example, offset 610 can be furtherdetermined based on measurement coordinates 620 substantially defining aportion of the measured contour 330. As used herein, the term“measurement coordinates” means coordinates that define some or all of ameasured contour. Measurement coordinates can be generated by theimaging device, by analysis of images taken by the imaging device, etc.For example, measurement coordinates can be pixel positions that havebeen determined to correspond to an edge of a contour. Accordingly, anedge detection program can generate measurement coordinates 620 based onimage processing of measured image 320. Examples of measurementcoordinates 620 are illustrated in FIG. 6 by circles on measured contour330.

In one embodiment, offset 610 can be further determined based ondistances between measurement coordinates 620 and simulated contour 510.In some specific embodiments, the distances can be in directionsperpendicular to measured contour 330 at measurement coordinates 620. Inother embodiments, the degree of alignment can be determined by forexample, summing the squares of distance of some or all offsets, orsumming some or all offsets. This can be performed, for example, withthe x-component and/or the y-component of the perpendicular offsetvector.

In some embodiments, the aligning can further include reducing a costfunction calculated based on the distances. Examples of cost functionsare described above (e.g., the description of Eqn. 1). A cost functioncan be reduced by, for example, fine adjustments to the position ofmeasured contour 330. When cost function is at a minimum (or otherwisesatisfactory value), the alignment of measured contour 330 to simulatedcontour 510 can be used for further processes or as a measure of theprocess model calibration.

To provide additional points for the alignment methods described herein,certain embodiments can include generating any number of additionalpoints (e.g., edge placement (EP) coordinates) on measured contour 330.As used herein, EP coordinate 630 (also referred to herein as an EPgauge), is an additional point that defines measured contour 330. Oneexample of EP coordinate 630 is illustrated in FIG. 6 by the solidsquare located on measured contour 330. In some embodiments, EPcoordinate 630 can be generated by interpolating between two or moremeasurement coordinates 620. In other embodiments, EP coordinate 630 canbe generated by extrapolating from two or more measurement coordinates620. Accordingly, offset 610 can be further determined based on EPcoordinate 630, alternatively or in addition to, measurement coordinates620.

In some embodiments, simulated contour 510 can be obtained from GraphicDatabase Systems (GDS) polygons, i.e., polygons generated by the processmodel and corresponding to a contour shape. In other embodiments, theGDS polygons can be in one or more formats selected from GDS streamformat (GDSII) and Open Artwork System Interchange Standard (OASIS).Then, as part of the calibration process, edge placement coordinates 630and/or measurement coordinates 620 comprising measured simulated contour510 can be converted into GDS coordinates. Such a conversion can allow amore direct comparison between simulated contour 510 and measuredcontour 330.

FIG. 7 illustrates an exemplary improvement of matching a simulatedcontour 510 to a measured contour 330, according to an embodiment.

The embodiments described herein can facilitate calibrating a processmodel to provide a more accurate match between a simulated contour 510(generated by the process model) and the measured contour 330. In someembodiments, calibrating the process model can include reducing adifference, computed based on a determined offset 610, between simulatedcontour 510 and measured contour 330.

As used herein, “difference” means a quantified measure of degree ofdeviation between two or more contours. One non-limiting example of adifference is the aforementioned cost function. Another example of adifference can also be the offset or distance between points on twocontours, without using them in a cost function.

In some embodiments, methods can include modifying a feature of theprocess model to reduce the difference. In some embodiments, themodifying can cause a change to a shape of simulated contour 510.Examples of features of the resist model that can be modified caninclude diffusion rate, diffusion range, deprotection ratio, andacid/base concentration. Modifications performed in this way can beconsidered a “fine-tuning” of the process model to improve its abilityto predict measured contours 330. In some embodiments, this can resultin an improved optical model, resist model, OPC model, etc.

FIG. 8 illustrates an exemplary improvement in alignment based onimproving a preliminary model 810, according to an embodiment.

Improving a process model, including an OPC model, can begin with apreliminary model 810 instead of, for example, a full process model. Forexample, some embodiments can include obtaining the simulated contour510 based on the simulation of the OPC model, where the OPC model can bepreliminary model 810. Preliminary model 810 can include a reducednumber of model components, for example, including an optical model andnot including a resist model.

In other embodiments, methods can include obtaining initial simulatedcontour 510 with improved preliminary model 820 (e.g., that includes anoptical model and a resist model). Specifically, some embodiments caninclude modifying features of the resist model to reduce the differencebetween the initial simulated contour 510 and the measured contour 330.Examples of features that can be modified can include diffusion rate,diffusion range, deprotection ratio, and acid/base concentration, asdescribed above with reference to a resist model. In this way, thepreliminary model 810 can be used and improved as described herein. Inother embodiments, modification to the preliminary model 810 cangenerate improved preliminary model 820 in turn generate simulatedcontours 510. Such iterative methods can provide increasingly improvedsimulated contours 510 for the alignment procedures described herein.

In some embodiments of the present disclosure, reduced processing timeand computational overhead have been realized. For example, byleveraging features including image-averaging (such as described withreference to FIG. 4) and accurate image alignment (such as describedwith reference to FIG. 3), computational time for image acquisition hasbeen reduced at least an order of magnitude, from days to hours. At thesame time, the model calibration time implementing these high quality EPgauges is about the same as when using CD gauges.

FIG. 9 illustrates an exemplary method of calibrating a process model,according to an embodiment.

In some embodiments, a method for improving a process model for apatterning process can include, at 910, obtaining a) measured contour330 from an image capture device, b) simulated contour 510 generatedfrom a simulation of the process model.

At 920, aligning measured contour 330 with simulated contour 510 bydetermining offset 610 between measured contour 330 and simulatedcontour 510.

At 930, calibrating the process model to reduce a difference, computedbased on determined offset 610, between simulated contour 510 andmeasured contour 330.

FIG. 10 illustrates an exemplary method of calibrating an OPC model,according to an embodiment.

In some embodiments, a method for improving an optical proximitycorrection (OPC) model for a patterning process can include, at 1010,obtaining a) measured contour 330 from image capture device, and b)simulated contour 510 generated from a simulation of the OPC model.

At 1020, aligning measured contour 330 with simulated contour 510 bydetermining offset 610 between measured contour 330 and simulatedcontour 510.

At 1030, modifying features of the OPC model to reduce a difference,computed based on determined offset 610, between simulated contour 510and measured contour 330.

FIG. 11 illustrates an exemplary method of acquiring multiple images ofa target and calibrating a process model, according to an embodiment.

In some embodiments, a method for improving a process model for apatterning process can include, at 1110, obtaining a) multiple measuredimages 410 from an image capture device, and b) simulated contour 510generated from a simulation of the process model.

At 1120, aligning multiple measured images 410.

At 1130, generating a combined measured image 320 from the alignedmultiple measured images 410.

At 1140, extracting measured contour 330 from combined measured image320 by an image analysis method.

At 1150, aligning measured contour 330 with simulated contour 510 bydetermining offset 610 between measured contour 330 and simulatedcontour 510.

At 1160, calibrating the process model to reduce a difference, computedbased on determined offset 610, between simulated contour 510 andmeasured contour 330.

FIG. 12 is a block diagram of an example metrology system, according toan embodiment. The embodiments described herein can be implemented onany number and combination of computing systems, image capture devices,servers, and user interfaces. One exemplary system is illustrated inFIG. 12, where cluster 1210, which may optionally contain any number ofcomputers operating in series and/or parallel, can be configured toallow selection and transmission of EP coordinates 630, also referred toherein as EP gauges 630. EP gauges 630 can be transmitted to one or moremanaging servers 1220, where recipe 1230 can be sent to image capturedevice 1240. Recipe 1230 can include information about the patterningprocess and also instructions for operation of image capture device1240. The exemplary systems thus described improve OPC predictionaccuracy and reduce OPC development cycle time.

FIG. 13 is a process flow diagram of an example implementation of animproved metrology process, according to an embodiment.

A method for improving metrology according to the systems andembodiments described herein can include executing a process model on acomputing cluster, such as cluster 1210. The process model can accept,at 1310, a reticle design. The process model can then generate, at 1312,a GDS layout specifying the target pattern. At 1314, the process modelcan then select one or more EP gauges, for example as described withreference to FIG. 6.

An image capture device, for example image capture device 1240, cangenerate, at 1320, recipe 1230. Recipe 1230 can be used by image capturedevice 1240 to perform, at 1322, high-quality metrology on the printedpattern, including generating any number of high-resolution measuredimages. Measured images can be transmitted to cluster 1210 for imageprocessing.

Image processing can include, for example, executing image filtering at1330, image alignment and averaging 1332, contour extraction 1334, andEP gauge extraction 1336. Image filtering can include, for example,automatic removal of misprinted images and/or low contrast images, basedfor example on permitted benchmarks or tolerances. Optionally, recipe1230 and measured images 320 can be input from 1322, as part of thecontour extraction process to increase metrology consistency bycomparing measured images 320 before and after the image filtering andaveraging alignment processes.

Model calibration and validation can be performed at 1340, where the EPgauges extracted at 1336 can be received by one or more computingsystems. The calibrated and validated model can be optimized, at 1340,to support a large number of EP gauges, for example an increase by afactor of 2, 3, 3.6, 5, 10, or more, over the number of CD gauges. At1342, the process model can be calibrated and at 1344, the calibratedprocess model can be provided to a graphical user interface (GUI) foruser review, refinement, transmission, or further processing.

FIG. 14 is a block diagram of an example computer system CS, accordingto an embodiment.

Computer system CS includes a bus BS or other communication mechanismfor communicating information, and a processor PRO (or multipleprocessor) coupled with bus BS for processing information. Computersystem CS also includes a main memory MM, such as a random access memory(RAM) or other dynamic storage device, coupled to bus BS for storinginformation and instructions to be executed by processor PRO. Mainmemory MM also may be used for storing temporary variables or otherintermediate information during execution of instructions to be executedby processor PRO. Computer system CS further includes a read only memory(ROM) ROM or other static storage device coupled to bus BS for storingstatic information and instructions for processor PRO. A storage deviceSD, such as a magnetic disk or optical disk, is provided and coupled tobus BS for storing information and instructions.

Computer system CS may be coupled via bus BS to a display DS, such as acathode ray tube (CRT) or flat panel or touch panel display fordisplaying information to a computer user. An input device ID, includingalphanumeric and other keys, is coupled to bus BS for communicatinginformation and command selections to processor PRO. Another type ofuser input device is cursor control CC, such as a mouse, a trackball, orcursor direction keys for communicating direction information andcommand selections to processor PRO and for controlling cursor movementon display DS. This input device typically has two degrees of freedom intwo axes, a first axis (e.g., x) and a second axis (e.g., y), thatallows the device to specify positions in a plane. A touch panel(screen) display may also be used as an input device.

According to one embodiment, portions of one or more methods describedherein may be performed by computer system CS in response to processorPRO executing one or more sequences of one or more instructionscontained in main memory MM. Such instructions may be read into mainmemory MM from another computer-readable medium, such as storage deviceSD. Execution of the sequences of instructions contained in main memoryMM causes processor PRO to perform the process steps described herein.One or more processors in a multi-processing arrangement may also beemployed to execute the sequences of instructions contained in mainmemory MM. In an alternative embodiment, hard-wired circuitry may beused in place of or in combination with software instructions. Thus, thedescription herein is not limited to any specific combination ofhardware circuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to processor PRO forexecution. Such a medium may take many forms, including but not limitedto, non-volatile media, volatile media, and transmission media.Non-volatile media include, for example, optical or magnetic disks, suchas storage device SD. Volatile media include dynamic memory, such asmain memory MM. Transmission media include coaxial cables, copper wireand fiber optics, including the wires that comprise bus BS. Transmissionmedia can also take the form of acoustic or light waves, such as thosegenerated during radio frequency (RF) and infrared (IR) datacommunications. Computer-readable media can be non-transitory, forexample, a floppy disk, a flexible disk, hard disk, magnetic tape, anyother magnetic medium, a CD-ROM, DVD, any other optical medium, punchcards, paper tape, any other physical medium with patterns of holes, aRAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip orcartridge. Non-transitory computer readable media can have instructionsrecorded thereon. The instructions, when executed by a computer, canimplement any of the features described herein. Transitorycomputer-readable media can include a carrier wave or other propagatingelectromagnetic signal.

Various forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to processor PRO forexecution. For example, the instructions may initially be borne on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system CS canreceive the data on the telephone line and use an infrared transmitterto convert the data to an infrared signal. An infrared detector coupledto bus BS can receive the data carried in the infrared signal and placethe data on bus BS. Bus BS carries the data to main memory MM, fromwhich processor PRO retrieves and executes the instructions. Theinstructions received by main memory MM may optionally be stored onstorage device SD either before or after execution by processor PRO.

Computer system CS may also include a communication interface CI coupledto bus BS. Communication interface CI provides a two-way datacommunication coupling to a network link NDL that is connected to alocal network LAN. For example, communication interface CI may be anintegrated services digital network (ISDN) card or a modem to provide adata communication connection to a corresponding type of telephone line.As another example, communication interface CI may be a local areanetwork (LAN) card to provide a data communication connection to acompatible LAN. Wireless links may also be implemented. In any suchimplementation, communication interface CI sends and receiveselectrical, electromagnetic or optical signals that carry digital datastreams representing various types of information.

Network link NDL typically provides data communication through one ormore networks to other data devices. For example, network link NDL mayprovide a connection through local network LAN to a host computer HC.This can include data communication services provided through theworldwide packet data communication network, now commonly referred to asthe “Internet” INT. Local network LAN (Internet) both use electrical,electromagnetic or optical signals that carry digital data streams. Thesignals through the various networks and the signals on network datalink NDL and through communication interface CI, which carry the digitaldata to and from computer system CS, are exemplary forms of carrierwaves transporting the information.

Computer system CS can send messages and receive data, including programcode, through the network(s), network data link NDL, and communicationinterface CI. In the Internet example, host computer HC might transmit arequested code for an application program through Internet INT, networkdata link NDL, local network LAN and communication interface CI. Onesuch downloaded application may provide all or part of a methoddescribed herein, for example. The received code may be executed byprocessor PRO as it is received, and/or stored in storage device SD, orother non-volatile storage for later execution. In this manner, computersystem CS may obtain application code in the form of a carrier wave.

FIG. 15 is a schematic diagram of a lithographic projection apparatus,according to an embodiment.

The lithographic projection apparatus can include an illumination systemIL, a first object table MT, a second object table WT, and a projectionsystem PS.

Illumination system IL, can condition a beam B of radiation. In thisparticular case, the illumination system also comprises a radiationsource SO.

First object table (e.g., patterning device table) MT can be providedwith a patterning device holder to hold a patterning device MA (e.g., areticle), and connected to a first positioner to accurately position thepatterning device with respect to item PS.

Second object table (substrate table) WT can be provided with asubstrate holder to hold a substrate W (e.g., a resist-coated siliconwafer), and connected to a second positioner to accurately position thesubstrate with respect to item PS.

Projection system (“lens”) PS (e.g., a refractive, catoptric orcatadioptric optical system) can image an irradiated portion of thepatterning device MA onto a target portion C (e.g., comprising one ormore dies) of the substrate W.

As depicted herein, the apparatus can be of a transmissive type (i.e.,has a transmissive patterning device). However, in general, it may alsobe of a reflective type, for example (with a reflective patterningdevice). The apparatus may employ a different kind of patterning deviceto classic mask; examples include a programmable mirror array or LCDmatrix.

The source SO (e.g., a mercury lamp or excimer laser, LPP (laserproduced plasma) EUV source) produces a beam of radiation. This beam isfed into an illumination system (illuminator) IL, either directly orafter having traversed conditioning means, such as a beam expander Ex,for example. The illuminator IL may comprise adjusting means AD forsetting the outer and/or inner radial extent (commonly referred to asσ-outer and σ-inner, respectively) of the intensity distribution in thebeam. In addition, it will generally comprise various other components,such as an integrator IN and a condenser CO. In this way, the beam Bimpinging on the patterning device MA has a desired uniformity andintensity distribution in its cross-section.

In some embodiments, source SO may be within the housing of thelithographic projection apparatus (as is often the case when source SOis a mercury lamp, for example), but that it may also be remote from thelithographic projection apparatus, the radiation beam that it producesbeing led into the apparatus (e.g., with the aid of suitable directingmirrors); this latter scenario can be the case when source SO is anexcimer laser (e.g., based on KrF, ArF or F2 lasing).

The beam PB can subsequently intercept patterning device MA, which isheld on a patterning device table MT. Having traversed patterning deviceMA, the beam B can pass through the lens PL, which focuses beam B ontotarget portion C of substrate W. With the aid of the second positioningmeans (and interferometric measuring means IF), the substrate table WTcan be moved accurately, e.g. so as to position different targetportions C in the path of beam PB. Similarly, the first positioningmeans can be used to accurately position patterning device MA withrespect to the path of beam B, e.g., after mechanical retrieval of thepatterning device MA from a patterning device library, or during a scan.In general, movement of the object tables MT, WT can be realized withthe aid of a long-stroke module (coarse positioning) and a short-strokemodule (fine positioning). However, in the case of a stepper (as opposedto a step-and-scan tool) patterning device table MT may just beconnected to a short stroke actuator, or may be fixed.

The depicted tool can be used in two different modes, step mode and scanmode. In step mode, patterning device table MT is kept essentiallystationary, and an entire patterning device image is projected in one go(i.e., a single “flash”) onto a target portion C. Substrate table WT canbe shifted in the x and/or y directions so that a different targetportion C can be irradiated by beam PB.

In scan mode, essentially the same scenario applies, except that a giventarget portion C is not exposed in a single “flash.” Instead, patterningdevice table MT is movable in a given direction (the so-called “scandirection”, e.g., the y direction) with a speed v, so that projectionbeam B is caused to scan over a patterning device image; concurrently,substrate table WT is simultaneously moved in the same or oppositedirection at a speed V=Mv, in which M is the magnification of the lensPL (typically, M=1/4 or 1/5). In this manner, a relatively large targetportion C can be exposed, without having to compromise on resolution.

FIG. 16 is a schematic diagram of another lithographic projectionapparatus (LPA), according to an embodiment.

LPA can include source collector module SO, illumination system(illuminator) IL configured to condition a radiation beam B (e.g. EUVradiation), support structure MT, substrate table WT, and projectionsystem PS.

Support structure (e.g. a patterning device table) MT can be constructedto support a patterning device (e.g. a mask or a reticle) MA andconnected to a first positioner PM configured to accurately position thepatterning device;

Substrate table (e.g. a wafer table) WT can be constructed to hold asubstrate (e.g. a resist coated wafer) W and connected to a secondpositioner PW configured to accurately position the substrate.

Projection system (e.g. a reflective projection system) PS can beconfigured to project a pattern imparted to the radiation beam B bypatterning device MA onto a target portion C (e.g. comprising one ormore dies) of the substrate W.

As here depicted, LPA can be of a reflective type (e.g. employing areflective patterning device). It is to be noted that because mostmaterials are absorptive within the EUV wavelength range, the patterningdevice may have multilayer reflectors comprising, for example, amulti-stack of molybdenum and silicon. In one example, the multi-stackreflector has a 40 layer pairs of molybdenum and silicon where thethickness of each layer is a quarter wavelength. Even smallerwavelengths may be produced with X-ray lithography. Since most materialis absorptive at EUV and x-ray wavelengths, a thin piece of patternedabsorbing material on the patterning device topography (e.g., a TaNabsorber on top of the multi-layer reflector) defines where featureswould print (positive resist) or not print (negative resist).

Illuminator IL can receive an extreme ultra violet radiation beam fromsource collector module SO. Methods to produce EUV radiation include,but are not necessarily limited to, converting a material into a plasmastate that has at least one element, e.g., xenon, lithium or tin, withone or more emission lines in the EUV range. In one such method, oftentermed laser produced plasma (“LPP”) the plasma can be produced byirradiating a fuel, such as a droplet, stream or cluster of materialhaving the line-emitting element, with a laser beam. Source collectormodule SO may be part of an EUV radiation system including a laser, notshown in FIG. 11, for providing the laser beam exciting the fuel. Theresulting plasma emits output radiation, e.g., EUV radiation, which iscollected using a radiation collector, disposed in the source collectormodule. The laser and the source collector module may be separateentities, for example when a CO2 laser is used to provide the laser beamfor fuel excitation.

In such cases, the laser may not be considered to form part of thelithographic apparatus and the radiation beam can be passed from thelaser to the source collector module with the aid of a beam deliverysystem comprising, for example, suitable directing mirrors and/or a beamexpander. In other cases, the source may be an integral part of thesource collector module, for example when the source is a dischargeproduced plasma EUV generator, often termed as a DPP source.

Illuminator IL may comprise an adjuster for adjusting the angularintensity distribution of the radiation beam. Generally, at least theouter and/or inner radial extent (commonly referred to as a-outer anda-inner, respectively) of the intensity distribution in a pupil plane ofthe illuminator can be adjusted. In addition, the illuminator IL maycomprise various other components, such as facetted field and pupilmirror devices. The illuminator may be used to condition the radiationbeam, to have a desired uniformity and intensity distribution in itscross section.

The radiation beam B can be incident on the patterning device (e.g.,mask) MA, which is held on the support structure (e.g., patterningdevice table) MT, and is patterned by the patterning device. After beingreflected from the patterning device (e.g. mask) MA, the radiation beamB passes through the projection system PS, which focuses the beam onto atarget portion C of the substrate W. With the aid of the secondpositioner PW and position sensor PS2 (e.g. an interferometric device,linear encoder or capacitive sensor), the substrate table WT can bemoved accurately, e.g. so as to position different target portions C inthe path of radiation beam B. Similarly, the first positioner PM andanother position sensor PS1 can be used to accurately position thepatterning device (e.g. mask) MA with respect to the path of theradiation beam B. Patterning device (e.g. mask) MA and substrate W maybe aligned using patterning device alignment marks M1, M2 and substratealignment marks P1, P2.

The depicted apparatus LPA could be used in at least one of thefollowing modes, step mode, scan mode, and stationary mode.

In step mode, the support structure (e.g. patterning device table) MTand the substrate table WT are kept essentially stationary, while anentire pattern imparted to the radiation beam is projected onto a targetportion C at one time (i.e. a single static exposure). The substratetable WT is then shifted in the X and/or Y direction so that a differenttarget portion C can be exposed.

In scan mode, the support structure (e.g. patterning device table) MTand the substrate table WT are scanned synchronously while a patternimparted to the radiation beam is projected onto target portion C (i.e.a single dynamic exposure). The velocity and direction of substratetable WT relative to the support structure (e.g. patterning devicetable) MT may be determined by the (de-)magnification and image reversalcharacteristics of the projection system PS.

In stationary mode, the support structure (e.g. patterning device table)MT is kept essentially stationary holding a programmable patterningdevice, and substrate table WT is moved or scanned while a patternimparted to the radiation beam is projected onto a target portion C. Inthis mode, generally a pulsed radiation source is employed and theprogrammable patterning device is updated as required after eachmovement of the substrate table WT or in between successive radiationpulses during a scan. This mode of operation can be readily applied tomaskless lithography that utilizes programmable patterning device, suchas a programmable mirror array of a type as referred to above.

FIG. 17 is a detailed view of the lithographic projection apparatus,according to an embodiment.

As shown, LPA can include the source collector module SO, theillumination system IL, and the projection system PS. The sourcecollector module SO is constructed and arranged such that a vacuumenvironment can be maintained in an enclosing structure 220 of thesource collector module SO. An EUV radiation emitting plasma 210 may beformed by a discharge produced plasma source. EUV radiation may beproduced by a gas or vapor, for example Xe gas, Li vapor or Sn vapor inwhich the very hot plasma 210 is created to emit radiation in the EUVrange of the electromagnetic spectrum. The very hot plasma 210 iscreated by, for example, an electrical discharge causing at leastpartially ionized plasma. Partial pressures of, for example, 10 Pa ofXe, Li, Sn vapor or any other suitable gas or vapor may be required forefficient generation of the radiation. In an embodiment, a plasma ofexcited tin (Sn) is provided to produce EUV radiation.

The radiation emitted by the hot plasma 210 is passed from a sourcechamber 211 into a collector chamber 212 via an optional gas barrier orcontaminant trap 230 (in some cases also referred to as contaminantbarrier or foil trap) which is positioned in or behind an opening insource chamber 211. The contaminant trap 230 may include a channelstructure. Contamination trap 230 may also include a gas barrier or acombination of a gas barrier and a channel structure. The contaminanttrap or contaminant barrier 230 further indicated herein at leastincludes a channel structure, as known in the art.

The collector chamber 211 may include a radiation collector CO which maybe a so-called grazing incidence collector. Radiation collector CO hasan upstream radiation collector side 251 and a downstream radiationcollector side 252. Radiation that traverses collector CO can bereflected off a grating spectral filter 240 to be focused in a virtualsource point IF along the optical axis indicated by the dot-dashed line‘O’. The virtual source point IF is commonly referred to as theintermediate focus, and the source collector module is arranged suchthat the intermediate focus IF is located at or near an opening 221 inthe enclosing structure 220. The virtual source point IF is an image ofthe radiation emitting plasma 210.

Subsequently the radiation traverses the illumination system IL, whichmay include a facetted field mirror device 22 and a facetted pupilmirror device 24 arranged to provide a desired angular distribution ofthe radiation beam 21, at the patterning device MA, as well as a desireduniformity of radiation intensity at the patterning device MA. Uponreflection of the beam of radiation 21 at the patterning device MA, heldby the support structure MT, a patterned beam 26 is formed and thepatterned beam 26 is imaged by the projection system PS via reflectiveelements 28, 30 onto a substrate W held by the substrate table WT.

More elements than shown may generally be present in illumination opticsunit IL and projection system PS. The grating spectral filter 240 mayoptionally be present, depending upon the type of lithographicapparatus. Further, there may be more mirrors present than those shownin the figures, for example there may be 1-6 additional reflectiveelements present in the projection system PS than shown in FIG. 12.

Collector optic CO, as illustrated in FIG. 12, is depicted as a nestedcollector with grazing incidence reflectors 253, 254 and 255, just as anexample of a collector (or collector mirror). The grazing incidencereflectors 253, 254 and 255 are disposed axially symmetric around theoptical axis O and a collector optic CO of this type may be used incombination with a discharge produced plasma source, often called a DPPsource.

FIG. 18 is a detailed view of source collector module SO of lithographicprojection apparatus LPA, according to an embodiment.

Source collector module SO may be part of an LPA radiation system. Alaser LA can be arranged to deposit laser energy into a fuel, such asxenon (Xe), tin (Sn) or lithium (Li), creating the highly ionized plasma210 with electron temperatures of several 10's of eV. The energeticradiation generated during de-excitation and recombination of these ionsis emitted from the plasma, collected by a near normal incidencecollector optic CO and focused onto the opening 221 in the enclosingstructure 220.

The concepts disclosed herein may simulate or mathematically model anygeneric imaging system for imaging sub wavelength features, and may beespecially useful with emerging imaging technologies capable ofproducing increasingly shorter wavelengths. Emerging technologiesalready in use include EUV (extreme ultra violet), DUV lithography thatis capable of producing a 193 nm wavelength with the use of an ArFlaser, and even a 157 nm wavelength with the use of a Fluorine laser.Moreover, EUV lithography is capable of producing wavelengths within arange of 20-50 nm by using a synchrotron or by hitting a material(either solid or a plasma) with high energy electrons in order toproduce photons within this range.

FIG. 19 schematically depicts an embodiment of an electron beaminspection apparatus 1920, according to an embodiment. In an embodiment,the inspection apparatus may be an electron beam inspection apparatus(e.g., the same as or similar to a scanning electron microscope (SEM))that yields an image of a structure (e.g., some or all the structure ofa device, such as an integrated circuit) exposed or transferred on thesubstrate. A primary electron beam 1924 emitted from an electron source1922 is converged by condenser lens 1926 and then passes through a beamdeflector 1928, an E×B deflector 1930, and an objective lens 1932 toirradiate a substrate 1910 on a substrate table 1912 at a focus.

When the substrate 1910 is irradiated with electron beam 1924, secondaryelectrons are generated from the substrate 1910. The secondary electronsare deflected by the E×B deflector 1930 and detected by a secondaryelectron detector 1934. A two-dimensional electron beam image can beobtained by detecting the electrons generated from the sample insynchronization with, e.g., two dimensional scanning of the electronbeam by beam deflector 1928 or with repetitive scanning of electron beam1924 by beam deflector 1928 in an X or Y direction, together withcontinuous movement of the substrate 1910 by the substrate table 1912 inthe other of the X or Y direction. Thus, in an embodiment, the electronbeam inspection apparatus has a field of view for the electron beamdefined by the angular range into which the electron beam can beprovided by the electron beam inspection apparatus (e.g., the angularrange through which the deflector 1928 can provide the electron beam1924). Thus, the spatial extent of the field of the view is the spatialextent to which the angular range of the electron beam can impinge on asurface (wherein the surface can be stationary or can move with respectto the field).

A signal detected by secondary electron detector 1934 is converted to adigital signal by an analog/digital (A/D) converter 1936, and thedigital signal is sent to an image processing system 1950. In anembodiment, the image processing system 1950 may have memory 1956 tostore all or part of digital images for processing by a processing unit1958. The processing unit 1958 (e.g., specially designed hardware or acombination of hardware and software or a computer readable mediumcomprising software) is configured to convert or process the digitalimages into datasets representative of the digital images. In anembodiment, the processing unit 1958 is configured or programmed tocause execution of a method described herein. Further, image processingsystem 1950 may have a storage medium 1956 configured to store thedigital images and corresponding datasets in a reference database. Adisplay device 1954 may be connected with the image processing system1950, so that an operator can conduct necessary operation of theequipment with the help of a graphical user interface.

FIG. 20 schematically illustrates a further embodiment of an inspectionapparatus, according to an embodiment. The system is used to inspect asample 90 (such as a substrate) on a sample stage 88 and comprises acharged particle beam generator 81, a condenser lens module 82, a probeforming objective lens module 83, a charged particle beam deflectionmodule 84, a secondary charged particle detector module 85, and an imageforming module 86.

The charged particle beam generator 81 generates a primary chargedparticle beam 91. The condenser lens module 82 condenses the generatedprimary charged particle beam 91. The probe forming objective lensmodule 83 focuses the condensed primary charged particle beam into acharged particle beam probe 92. The charged particle beam deflectionmodule 84 scans the formed charged particle beam probe 92 across thesurface of an area of interest on the sample 90 secured on the samplestage 88. In an embodiment, the charged particle beam generator 81, thecondenser lens module 82 and the probe forming objective lens module 83,or their equivalent designs, alternatives or any combination thereof,together form a charged particle beam probe generator which generatesthe scanning charged particle beam probe 92.

The secondary charged particle detector module 85 detects secondarycharged particles 93 emitted from the sample surface (maybe also alongwith other reflected or scattered charged particles from the samplesurface) upon being bombarded by the charged particle beam probe 92 togenerate a secondary charged particle detection signal 94. The imageforming module 86 (e.g., a computing device) is coupled with thesecondary charged particle detector module 85 to receive the secondarycharged particle detection signal 94 from the secondary charged particledetector module 85 and accordingly forming at least one scanned image.In an embodiment, the secondary charged particle detector module 85 andimage forming module 86, or their equivalent designs, alternatives orany combination thereof, together form an image forming apparatus whichforms a scanned image from detected secondary charged particles emittedfrom sample 90 being bombarded by the charged particle beam probe 92.

In an embodiment, a monitoring module 87 is coupled to the image formingmodule 86 of the image forming apparatus to monitor, control, etc. thepatterning process and/or derive a parameter for patterning processdesign, control, monitoring, etc. using the scanned image of the sample90 received from image forming module 86. So, in an embodiment, themonitoring module 87 is configured or programmed to cause execution of amethod described herein. In an embodiment, the monitoring module 87comprises a computing device. In an embodiment, the monitoring module 87comprises a computer program to provide functionality herein and encodedon a computer readable medium forming, or disposed within, themonitoring module 87.

In an embodiment, like the electron beam inspection tool of FIG. 19 thatuses a probe to inspect a substrate, the electron current in the systemof FIG. 20 is significantly larger compared to, e.g., a CD SEM such asdepicted in FIG. 19, such that the probe spot is large enough so thatthe inspection speed can be fast. However, the resolution may not be ashigh as compared to a CD SEM because of the large probe spot.

The SEM images, from, e.g., the system of FIG. 19 and/or FIG. 20, may beprocessed to extract contours that describe the edges of objects,representing device structures, in the image. These contours are thentypically quantified via metrics, such as CD, at user-defined cut-lines.Thus, typically, the images of device structures are compared andquantified via metrics, such as an edge-to-edge distance (CD) measuredon extracted contours or simple pixel differences between images.Alternatively, metrics can include EP gauges as described herein.

The embodiments may further be described using the following clauses:

-   -   1. A method for improving a process model for a patterning        process, the method comprising: obtaining a) a measured contour        from an image capture device, and b) a simulated contour        generated from a simulation of the process model; aligning the        measured contour with the simulated contour by determining an        offset between the measured contour and the simulated contour;        and calibrating the process model to reduce a difference,        computed based on the determined offset, between the simulated        contour and the measured contour.    -   2. The method of clause 1, wherein the offset is further        determined based on measurement coordinates substantially        defining a portion of the measured contour.    -   3. The method of clause 2, wherein the offset is further        determined based on distances between the measurement        coordinates and the simulated contour, the distances being in        directions perpendicular to the measured contour at the        measurement coordinates.    -   4. The method of clause 3, the aligning further comprising        reducing a cost function calculated based on the distances.    -   5. The method as in any preceding clause, further comprising        generating an edge placement (EP) coordinate on the measured        contour, and wherein the offset is further determined based on        the EP coordinate.    -   6. The method of clause 4, wherein the EP coordinate is        generated by interpolating between two or more measurement        coordinates.    -   7. The method of clause 5, wherein the EP coordinate is        generated by extrapolating from two or more measurement        coordinates.    -   8. The method as in any preceding clause, the calibrating        further comprising modifying a feature of the process model to        reduce the difference, the modifying causing a change to a shape        of the simulated contour.    -   9. The method as in any preceding clause, wherein the measured        contour is identified based on a change in intensity of pixels        in the measured image.    -   10. The method of clause 7, wherein the identifying is based on        the change exceeding a greyscale threshold.    -   11. The method as in any preceding clause, further comprising:        -   obtaining the simulated contour from Graphic Database            Systems (GDS) polygons; and        -   converting edge placement coordinates or measurement            coordinates comprising the measured contour into GDS            coordinates.    -   12. The method of clause 9, wherein the GDS polygons can be in        one or more formats selected from GDS stream format (GDSII) and        Open Artwork System Interchange Standard (OASIS).    -   13. A method for improving an optical proximity correction (OPC)        model for a patterning process, the method comprising:        -   obtaining a) a measured contour from an image capture            device, and b) a simulated contour generated from a            simulation of the OPC model;        -   aligning the measured contour with the simulated contour by            determining an offset between the measured contour and the            simulated contour; and        -   modifying features of the OPC model to reduce a difference,            computed based on the determined offset, between the            simulated contour and the measured contour.    -   14. The method of clause Error! Reference source not found.,        wherein the features include one or more of a diffusion rate, a        diffusion range, a deprotection ratio, and an acid/base        concentration.    -   15. The method of any of clauses 13-14, further comprising:        -   obtaining the simulated contour based on the simulation of            the OPC model, wherein the OPC model is a preliminary model            that includes an optical model and does not include a resist            model.    -   16. The method of any of clauses 13-15, further comprising:        -   obtaining an initial simulated contour with a preliminary            model that includes an optical model and a resist model;        -   modifying features of the resist model to reduce the            difference between the initial simulated contour and the            measured contour.    -   17. A method for improving a process model for a patterning        process, the method comprising:        -   obtaining a) a plurality of measured images from an image            capture device, and b) a simulated contour generated from a            simulation of the process model;        -   aligning the plurality of measured images;        -   generating a combined measured image from the aligned            plurality of measured images; extracting a measured contour            from the combined measured image by an image analysis            method;        -   aligning the measured contour with the simulated contour by            determining an offset between the measured contour and the            simulated contour; and        -   calibrating the process model to reduce a difference,            computed based on the determined offset, between the            simulated contour and the measured contour.    -   18. The method of clause Error! Reference source not found.,        wherein the combined image is generated by averaging the aligned        plurality of measured images.    -   19. The method of any of clauses 17-18, wherein the plurality of        measured images are obtained from printed patterns from at least        two different dies manufactured from a target pattern.    -   20. The method of any of clauses 17-19, wherein each of the        plurality of measured images generating the combined image is        acquired by scanning a different die.    -   21. The method of any of clauses 17-20, wherein the image        capture device is a scanning electron microscope.    -   22. The method of clause Error! Reference source not found.,        wherein the obtaining of the plurality of measured images is        performed by scanning an electron beam over a printed pattern at        a plurality of angles.    -   23. The method of clause Error! Reference source not found.,        wherein the plurality of angles include approximately +45        degrees and −45 degrees.    -   24. The method of clause Error! Reference source not found. or        23, wherein half of the plurality of measured images are scanned        at approximately +45 degrees and another half of the plurality        of measured images are scanned at approximately −45 degrees.    -   25. The method of any of clauses 21 to 24, wherein the obtaining        is performed with the scanning electron microscope operating at        a dosage below that required to obtain a scan sufficient to        resolve a critical dimension.    -   26. The method of any of clauses 17-25, wherein the image        capture device is an electron beam inspection system.    -   27. The method of clause Error! Reference source not found.,        wherein the electron beam inspection system has a large field of        view and the plurality of measured images are obtained at least        partially from within the large field of view.    -   28. The method of clause Error! Reference source not found.,        wherein the large field of view is approximately 1-50 microns on        a side.    -   29. The method of clause Error! Reference source not found. or        28, wherein the large field of view is approximately 6-12        microns on a side.    -   30. The method of any of clauses Error! Reference source not        found. to 29, further comprising detecting, with the electron        beam inspection system, hotspots or weak-points in a printed        pattern.    -   31. The method of any of clauses 17-30, the method further        comprising: determining a common area in the plurality of        measured images captured from the image capture device; and        generating the combined measured image based on the common area.    -   32. A computer program product comprising a non-transitory        computer readable medium having instructions recorded thereon,        the instructions when executed by a computer implementing the        method of any of the above clauses.

Now, besides measuring substrates in a patterning process, it is oftendesirable to use one or more tools to produce results that, for example,can be used to design, control, monitor, etc. the patterning process. Todo this, there may be provided one or more tools used in computationallycontrolling, designing, etc. one or more aspects of the patterningprocess, such as the pattern design for a patterning device (including,for example, adding sub-resolution assist features or optical proximitycorrections), the illumination for the patterning device, etc.Accordingly, in a system for computationally controlling, designing,etc. a manufacturing process involving patterning, the majormanufacturing system components and/or processes can be described byvarious functional modules. In particular, in an embodiment, one or moremathematical models can be provided that describe one or more stepsand/or apparatuses of the patterning process, including typically thepattern transfer step. In an embodiment, a simulation of the patterningprocess can be performed using one or more mathematical models tosimulate how the patterning process forms a patterned substrate using ameasured or design pattern provided by a patterning device.

While the concepts disclosed herein may be used for imaging on asubstrate such as a silicon wafer, it shall be understood that thedisclosed concepts may be used with any type of lithographic imagingsystems, e.g., those used for imaging on substrates other than siliconwafers.

The descriptions above are intended to be illustrative, not limiting.Thus, it will be apparent to one skilled in the art that modificationsmay be made as described without departing from the scope of the claimsset out below.

1. A method for improving a process model for a patterning process, themethod comprising: obtaining a) a measured contour from an image capturedevice, and b) a simulated contour generated from a simulation of theprocess model; aligning the measured contour with the simulated contourby determining an offset between the measured contour and the simulatedcontour; and calibrating the process model to reduce a difference,computed based on the determined offset, between the simulated contourand the measured contour.
 2. The method of claim 1, wherein the offsetis further determined based on measurement coordinates substantiallydefining a portion of the measured contour.
 3. The method of claim 2,wherein the offset is further determined based on distances between themeasurement coordinates and the simulated contour, the distances beingin directions perpendicular to the measured contour at the measurementcoordinates.
 4. The method of claim 1, further comprising generating anedge placement (EP) coordinate on the measured contour, and wherein theoffset is further determined based on the EP coordinate.
 5. The methodof claim 4, wherein the EP coordinate is generated by interpolatingbetween two or more measurement coordinates, and/or wherein the EPcoordinate is generated by extrapolating from two or more measurementcoordinates.
 6. The method of claim 1, wherein the calibrating furthercomprises modifying a feature of the process model to reduce thedifference, the modifying causing a change to a shape of the simulatedcontour.
 7. The method of claim 1, wherein the measured contour isidentified based on a change in intensity of pixels in a measured imagefrom a plurality of measured images.
 8. The method of claim 7, whereinthe measured contour is identified based on the change exceeding agreyscale threshold.
 9. The method of claim 1, further comprising:obtaining the simulated contour from Graphic Database Systems (GDS)polygons; and converting edge placement coordinates or measurementcoordinates comprising the measured contour into GDS coordinates. 10.(canceled)
 11. The method of claim 1, further comprising obtaining thesimulated contour based on a simulation of an optical proximitycorrection (OPC) model, wherein the OPC model is a preliminary modelthat includes an optical model and does not include a resist model. 12.The method of claim 1, further comprising: obtaining an initialsimulated contour with a preliminary model that includes an opticalmodel and a resist model; and modifying features of the resist model toreduce a difference between the initial simulated contour and themeasured contour.
 13. The method of claim 1, wherein the image capturedevice is a scanning electron microscope.
 14. The method of claim 7,wherein the image capture device is an electron beam inspection system,and/or wherein the electron beam inspection system has a large field ofview and the plurality of measured images are obtained at leastpartially from within the large field of view.
 15. A computer programproduct comprising a non-transitory computer readable medium havinginstructions therein, the instructions, when executed by a computersystem, configured to cause the computer system to at least: obtain a) ameasured contour from an image capture device, and b) a simulatedcontour generated from a simulation of the process model; align themeasured contour with the simulated contour by determining an offsetbetween the measured contour and the simulated contour; and calibrate aprocess model for a patterning process to reduce a difference, computedbased on the determined offset, between the simulated contour and themeasured contour.
 16. The computer program product of claim 15, whereinthe offset is further determined based on measurement coordinatessubstantially defining a portion of the measured contour.
 17. Thecomputer program product of claim 16, wherein the offset is furtherdetermined based on distances between the measurement coordinates andthe simulated contour, the distances being in directions perpendicularto the measured contour at the measurement coordinates.
 18. The computerprogram product of claim 15, wherein the instructions are furtherconfigured to cause computer system to generate an edge placement (EP)coordinate on the measured contour, and wherein the offset is furtherdetermined based on the EP coordinate.
 19. The computer program productof claim 18, wherein the EP coordinate is generated by interpolatingbetween two or more measurement coordinates, and/or wherein the EPcoordinate is generated by extrapolating from two or more measurementcoordinates.
 20. The computer program product of claim 15, wherein theinstructions configured to cause the computer system to calibrate theprocess model are further configured to cause the computer system tomodify a feature of the process model to reduce the difference, themodification causing a change to a shape of the simulated contour. 21.The computer program product of claim 15, wherein the measured contouris identified based on a change in intensity of pixels in a measuredimage from a plurality of measured images.